CN117171516A - Data optimization correction method for X-ray thickness gauge - Google Patents
Data optimization correction method for X-ray thickness gauge Download PDFInfo
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Abstract
The invention relates to the technical field of thickness measurement, and provides an X-ray thickness meter data optimization correction method, which comprises the following steps: acquiring a monitoring data time sequence of all monitoring data; acquiring a modal component decomposition result of each voltage value sequence converted by the environmental noise sound wave by using an empirical mode decomposition algorithm; acquiring a first characteristic coefficient of measurement interference according to the amplitude difference between corresponding spectrograms of different modal components in the decomposition result; acquiring a measurement interference confidence coefficient according to the measurement interference first characteristic coefficient of each modal component of the voltage value sequence converted by different environmental noise sound waves; acquiring the wavelet decomposition layer number according to the measurement interference confidence coefficient; obtaining a clean current signal based on the wavelet decomposition layer number by utilizing a wavelet denoising algorithm; and obtaining a correction result of the thickness gauge data according to the clean current signal. According to the invention, the number of decomposition layers in the wavelet denoising algorithm is adaptively set, so that the deviation of a current signal caused by the interference of environmental noise on the thickness gauge is corrected.
Description
Technical Field
The invention relates to the technical field of thickness measurement, in particular to an X-ray thickness meter data optimization correction method.
Background
With the rapid development of science and technology, the demands for high-sophisticated technology and high-tech products are also increasing. In the field of metallurgical thickness measurement, the X-ray thickness gauge has been widely applied, meets the requirements of high-end fields such as automobiles, electronic instruments, aerospace equipment and the like on the thickness of the metal sheet, and improves the efficiency and the accuracy of the thickness measurement of the metal sheet. Compared with an infrared thickness gauge and an ultrasonic thickness gauge, the X-ray thickness gauge has the advantages of being high in stability and high in anti-interference capability, and plays an extremely important role in the field of metallurgical thickness measurement.
Although the X-ray thickness gauge has many advantages, there is also a problem of low measurement accuracy in coping with complex scenes. The improvement of the measurement precision of the X-ray thickness gauge is mostly the parameter compensation of the equipment, and the measurement precision is improved by reducing the influence of interference factors of the equipment. However, in the using process of the X-ray thickness measurement, the attenuation signal of the X-ray energy is converted into a current signal for measurement, the converted current signal is generally weak and is easily interfered by a noise signal in a measuring environment, so that the noise interference exists in the current signal, the signal characteristics in an actual application scene are not considered in the traditional data processing algorithm, the accuracy of noise reduction processing of a detection signal is low, and the measuring accuracy of the X-ray thickness meter is influenced.
Disclosure of Invention
The invention provides a data optimization correction method of an X-ray thickness gauge, which aims to solve the problem that the thickness of a metal plate to be measured is greatly measured by the X-ray thickness gauge due to the interference of environmental noise, and adopts the following technical scheme that:
the invention relates to a data optimization correction method for an X-ray thickness gauge, which comprises the following steps of:
acquiring a monitoring data time sequence of all monitoring data, wherein the monitoring data comprises a current value converted by X-ray intensity and a voltage value converted by environmental noise sound waves;
acquiring a modal component decomposition result corresponding to each voltage value sequence converted by the environmental noise sound wave by using an empirical mode decomposition algorithm; acquiring a first characteristic coefficient of measurement interference of each modal component according to the amplitude difference between corresponding spectrograms of different modal components in the decomposition result;
acquiring a measurement interference confidence coefficient according to the measurement interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the sound waves of the environmental noise;
acquiring the wavelet decomposition layer number according to the measurement interference confidence coefficient; obtaining a clean current signal based on the wavelet decomposition layer number by utilizing a wavelet denoising algorithm; and obtaining a correction result of the thickness gauge data according to the clean current signal.
Preferably, the method for obtaining the modal component decomposition result corresponding to the voltage value sequence converted by each environmental noise sound wave by using the empirical mode decomposition algorithm comprises the following steps:
and taking the voltage value sequence converted by each environmental noise sound wave as the input of an empirical mode decomposition algorithm, and acquiring a preset number of mode components corresponding to the voltage value sequence by using the empirical mode decomposition algorithm.
Preferably, the method for obtaining the first characteristic coefficient of the measurement interference of each modal component according to the amplitude difference between the corresponding spectrograms of different modal components in the decomposition result includes:
acquiring a measured interference coefficient and a measured interference difference coefficient of each modal component according to a spectrogram of each modal component in a modal component decomposition result corresponding to each voltage value sequence converted by the sound waves of the environmental noise;
taking the difference value of the measured interference coefficient between each modal component and any one of the rest modal components as a first difference value; taking the difference value between the measured interference difference coefficient between each modal component and any one of the rest modal components as a second difference value; the sum of the products of the first difference and the second difference over all the remaining one modal component is taken as the measured interference first characteristic coefficient for each modal component.
Preferably, the method for obtaining the measured interference coefficient and the measured interference difference coefficient of each modal component according to the spectrogram of each modal component in the modal component decomposition result corresponding to each voltage value sequence converted by the sound wave of the environmental noise includes:
carrying out Fourier transform on each modal component to obtain a spectrogram of each modal component, and taking an amplitude corresponding to a frequency minimum value in the spectrogram of each modal component as a measurement interference coefficient of each modal component;
and taking the difference value between the maximum amplitude value and the minimum amplitude value in the spectrogram of each modal component as a measured interference difference coefficient of each modal component.
Preferably, the method for obtaining the measurement interference confidence coefficient according to the measurement interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the sound waves of the environmental noise includes:
acquiring a first characteristic difference sequence of each voltage value sequence converted by the environmental noise sound waves according to the measured interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the environmental noise sound waves;
acquiring interference complexity between two environmental noise sound waves according to a first characteristic difference sequence of a voltage value sequence converted by the two environmental noise sound waves;
taking the average value of interference complexity among all the environmental noise sound waves as a measurement interference confidence coefficient.
Preferably, the method for obtaining the first characteristic difference sequence of each voltage value sequence converted by the sound wave of the environmental noise according to the first characteristic coefficient of the measurement interference of each modal component corresponding to each voltage value sequence converted by the sound wave of the environmental noise comprises the following steps:
the measurement interference first characteristic difference coefficient of each modal component of each voltage value sequence converted by the environmental noise sound wave is used as the first characteristic difference sequence of the voltage value sequence converted by the environmental noise sound wave according to the sequence formed by the small-to-large sequence.
Preferably, the method for obtaining the interference complexity between the two environmental noise sound waves according to the first characteristic difference sequence of the voltage value sequences converted by the two environmental noise sound waves comprises the following steps:
taking the measurement distance between the first characteristic difference sequences of the two voltage value sequences converted by the sound waves of the environmental noise as a first interference difference value;
taking the difference value between the average values of the elements in the first characteristic difference sequence of the two voltage value sequences converted by the sound waves of the environmental noise as a second interference difference value;
the interference complexity between two environmental noise sound waves consists of a first interference difference value and a second interference difference value, wherein the interference complexity is in direct proportion to the first interference difference value and the second interference difference value.
Preferably, the method for obtaining the wavelet decomposition layer number according to the measurement interference confidence coefficient comprises the following steps:
taking the product of the measured interference confidence coefficient and the preset parameter as the input of a rounding function, and taking the output of the rounding function as the number of layers of wavelet decomposition.
Preferably, the method for obtaining the clean current signal based on the wavelet decomposition layer number by using the wavelet denoising algorithm comprises the following steps:
and taking the current signal acquired in the receiver of the thickness gauge as the input of a wavelet denoising algorithm, and obtaining a clean current signal based on the number of layers of the obtained wavelet decomposition by using the wavelet denoising algorithm.
Preferably, the method for obtaining the correction result of the thickness gauge data according to the clean current signal comprises the following steps:
and processing the clean current signal by a signal conversion unit and a computer in the X-ray thickness meter to obtain a measurement result of the metal plate to be measured as a correction result of the thickness meter data.
The beneficial effects of the invention are as follows: according to the invention, the complexity of environmental noise in different directions in the measurement process of the X-ray thickness gauge is analyzed, the noise complexity analysis result in each direction is synthesized to calculate the measurement interference confidence coefficient, and the number of decomposition layers in the wavelet denoising algorithm is obtained based on the measurement interference confidence coefficient.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of an optimized correction method for X-ray thickness meter data according to an embodiment of the present invention;
fig. 2 is a schematic diagram showing the relative positions of a sound sensor and a receiver according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flowchart of a method for optimizing and correcting data of an X-ray thickness gauge according to an embodiment of the invention is shown, and the method includes the following steps:
step S001, obtaining a monitoring data time sequence of all monitoring data.
The X-ray thickness gauge mainly comprises a transmitter, a receiver, a signal conversion unit, a computer processing unit and the like, wherein the receiver mainly converts the X-ray intensity into a current signal through an ionization chamber detector, and the current converted in the processThe signal intensity is weaker and is easy to be interfered by external environmental noise, so that sound sensors are arranged in four directions of a receiver to collect environmental noise monitoring data, sound waves generated by a noise source are received by the sound sensors, and voltage values generated by sound wave patterns or vibration of internal elements of the sensors are output. Meanwhile, current value monitoring data converted from X-ray intensity are collected through a current sensor, the time interval for collecting each monitoring data is t, each monitoring data is collected n times, the types of a sound sensor and the current sensor can be selected according to actual conditions, in the invention, the t is a tested value 1s, the n is an empirical value 600, a sequence formed by each monitoring data according to the sequence of time ascending is taken as a time sequence corresponding to each monitoring data, and the time sequences of four sound sensors are respectively recorded as a first monitoring data time sequenceSecond monitoring data time sequence->Third monitoring data time series->Fourth monitoring data time series->The time sequence of the current sensor is recorded as a current monitoring data sequence, < >>Wherein->Is the voltage value output by the first sound sensor for the first time.
So far, the time sequence of each monitoring data in the working process of the thickness gauge is obtained.
Step S002, a modal component decomposition result corresponding to the monitoring data time sequence is obtained, and a first characteristic coefficient of measurement interference is obtained based on the difference of the amplitude values on the spectrograms corresponding to different modal components.
The thickness of the metal plate to be measured is measured by the attenuation characteristic of the energy of the emitted X-rays passing through the metal plate to be measured, the X-rays reach the receiver after passing through the metal plate, the energy of the X-rays can be converted into current signals through conversion processing, the converted current signals are weak and are easy to be interfered by environmental noise, the interference influence of the current signals after being processed by the amplifier is amplified, and the X-ray thickness meter generates larger error on the measurement result of the thickness of the metal plate to be measured.
Firstly, analyzing the complexity of the working environment of the X-ray thickness gauge according to the monitoring data collected by the sound sensors at different positions, and if noise interference existing in the working environment of the X-ray thickness gauge is complex, the larger the possibility of larger deviation in the thickness measurement is. Analyzing the characteristics of the environmental noise data acquired at different positions according to the time sequences of the monitoring data, taking the time sequence of the first monitoring data as an example for each time sequence of the monitoring data, and adopting an Empirical Mode Decomposition (EMD) algorithm to perform EMD on the time sequence of the first monitoring dataProcessing, wherein the input is the first monitoring data time sequence, and the output is +.>The magnitude of y in the invention takes the tested value 8, further, each modal component in the analysis result is subjected to Fourier transformation to obtain a spectrogram of each modal component in the time sequence analysis result of the first monitoring data, and the first modal component is converted into the first modal componentThe spectrograms corresponding to the eighth mode component are respectively marked as +.>-/>The specific calculation process of the empirical mode decomposition algorithm and the fourier transform is a known technology, and will not be described in detail.
For each modal component in the first monitoring data time series decomposition result, taking the fundamental frequency component in the spectrogram of each modal component, namely the amplitude of the lowest frequency in the spectrogram, as the measured interference coefficient of each modal componentTaking the difference between the maximum value and the minimum value of the amplitude of each modal component as the measurement interference difference coefficient of each modal component +.>. When noise interference exists in the working environment of the thickness gauge, the larger the amplitude variation difference of noise signals on different frequencies and time scales in the decomposition result of each corresponding modal component is due to noise instability. Thus based on the measured interference coefficient +.f for each modal component in each monitored data time series decomposition result>Measuring interference difference coefficient->Acquiring a first characteristic coefficient of measurement interference of each modal component, which is used for representing noise conditions of different modal components corresponding to each monitoring data time sequence, and calculating the first characteristic coefficient of measurement interference of the first modal component in the first monitoring data time sequence decomposition result：
In the method, in the process of the invention,、/>the first monitoring data time sequence decomposition result is the measured interference coefficient, the measured interference difference coefficient and the +.>、/>The measured interference coefficient and the measured interference difference coefficient of the xth modal component in the first monitored data time series decomposition result are respectively, and y is the number of modal components in the first monitored data time series decomposition result.
The noise sensitivity in the working environment of the thickness gauge is high, so when the noise in the working environment of the thickness gauge is complex, the more obvious the characteristic of the noise signal on the same frequency and time scale is, the larger the difference of the discrete characteristic on other frequency and time scales is, the first difference value isThe greater the value of (2); while the larger the difference in amplitude variation of the noise signal at different frequencies and time scales, the second difference +.>The greater the value of (2); i.e. measuring interference first characteristic coefficient +.>The larger the value of (2) is, the 1 st modal component representing the first monitored data time series +.>The greater the difference in the noise signal characteristics of the presented noise signal characteristics from the noise signal characteristics of the other modal components.
So far, the first characteristic coefficient of measurement interference of each modal component in each monitoring data time sequence decomposition result is obtained and is used for calculating the confidence coefficient of subsequent measurement interference.
Step S003, obtaining a measurement interference confidence coefficient according to the measurement interference first characteristic coefficient of each modal component corresponding to different monitoring data time sequences.
According to the steps, the measurement interference first characteristic coefficient of each modal component in the decomposition result of each monitoring data time sequence is obtained, and because a single modal component can only reflect the signal information of part of frequencies in each monitoring data time sequence, in order to integrally characterize the signal information of all frequencies in each monitoring data time sequence, further, the measurement interference first characteristic coefficient of different modal components is utilized to construct the characteristic sequence of each monitoring data time sequence.
Taking the measured interference first characteristic difference coefficient of each modal component of the first monitoring data time sequence as a first characteristic difference sequence of the first monitoring data time sequence according to a sequence formed by sorting from small to largeThe first characteristic difference sequence of the first monitored data time sequence may be utilized to reflect the measured disturbance complex characteristic of the first monitored data time sequence. First characteristic difference sequence from the first monitoring data time sequence +.>The acquisition modes of the first and second monitoring data time sequences are the same, and the first characteristic difference sequences of the second monitoring data time sequence, the third monitoring data time sequence and the fourth monitoring data time sequence can be obtained and respectively recorded as、/>、/>. According to measuring interference first characteristicsThe difference sequence further analyzes the complex condition of the environmental noise interference measured by the X-ray thickness meter.
The first characteristic difference sequence can reflect the complexity degree of noise contained in the noise of the working environment where the X-ray thickness gauge is located, so that the interference complexity degree of the environment where the X-ray thickness gauge is located can be comprehensively analyzed through noise signal data collected by sound sensors at different positions, if the monitoring data time sequences at different positions contain different degrees of interference noise, the interference suffered by the thickness gauge in the measuring process is unstable, and the accuracy rate of the finally converted current signal is lower.
Here, a measurement interference confidence coefficient is constructedFor characterizing the noise interference degree of X-ray thickness meter in the working environment, measuring interference confidence coefficient +.>The calculation formula of (2) is as follows:
in the method, in the process of the invention,measurement interference confidence coefficient representing the environment of the X-ray thickness gauge, < ->And->Respectively represent the firstPerson and->A first characteristic difference sequence of the monitored data time series, and (2)>For the sequence->、/>DTW distance between>、/>Respectively representing the first characteristic difference sequence->、/>Mean value of the elements>The number of the first characteristic difference sequences is represented, in the present invention, the value of h is 4, the dtw distance is a known technology, and the specific process is not repeated.
The higher the complexity of the interference noise signal in the environment where the X-ray thickness gauge is located, the different environmental noises collected from different positions are, the different frequencies of the noise signals contained in the monitoring data time sequences obtained by the sound sensors at different positions are, the larger the difference between the first characteristic difference sequences is, and the first interference difference value isThe greater the value of (2); the longer the audio time collected at the same position, the more unstable the size of the elements in the time sequence of the collected monitoring data, the second interference difference value +.>The greater the value of (2); i.e. measuring interference confidence coefficient +.>The larger the value of (C) is, the greater the noise signal interference complexity of the environment where the X-ray thickness meter is located isThe measurement result is greatly affected when the thickness of the metal plate to be measured is measured.
So far, the measurement interference confidence coefficient is obtained and used for correcting the measurement result of the subsequent thickness gauge.
And S004, determining the wavelet decomposition layer number according to the measurement interference confidence coefficient, obtaining a clean current signal based on the wavelet decomposition layer number by utilizing a wavelet denoising algorithm, and obtaining a correction result of the thickness gauge data according to the clean current signal.
The measurement interference confidence coefficient is obtained according to the steps, and the influence degree of the X-ray thickness gauge on the interference noise in the environment where the X-ray thickness gauge is located is reflected. The more complex the environmental noise of the working environment of the X-ray thickness gauge is, the more complex the influence of noise signals on the characteristics of current signals in the measuring process is, the more the noise-removing processing should be carried out on the collected current monitoring data sequence, and when the noise-removing processing is carried out on the current monitoring data sequence by utilizing a wavelet noise-removing algorithm, the number of layers of the current monitoring data sequence which is obtained in the measuring process of the X-ray thickness gauge and is obtained in a self-adaptive mode according to the influence degree of the noise on the data, namely the measuring interference confidence coefficient, is obtained, and the correction of the measuring data of the thickness gauge is realized by eliminating the influence of noise to the greatest extent while preventing the current monitoring data sequence from being excessively decomposed.
The number of decomposition layers in the wavelet denoising algorithm is determined according to the measured interference confidence coefficient, and the specific calculation formula is as follows:
in the method, in the process of the invention,representing the number of decomposition layers in a wavelet denoising algorithm; />Representing the measurement interference confidence coefficient,/->Representing adjustment parametersNumber for adjusting the number of layers, +.>The magnitude of (2) takes the empirical value of 3,/j>Representing a round-up function.
When the X-ray thickness gauge measures a metal plate to be measured, X-rays emitted by a ray device of the X-ray thickness gauge are detected and converted into current signals by a detector in an ionization chamber, so that the current signals in the ionization chamber are used as input of a wavelet denoising algorithm, the number of decomposition layers in the wavelet denoising algorithm is set to be M, the wavelet denoising algorithm is used for obtaining clean current signals after denoising, and the specific process is not repeated. Amplifying and converting a clean current signal into a voltage signal through a signal processing circuit, supplying the voltage signal to a sampling circuit, and obtaining a measured value H of the thickness of the metal plate to be measured by utilizing the voltage value output by the sampling circuit:
in the method, in the process of the invention,is the effective attenuation coefficient of the metal plate to be tested, < >>Is to measure the voltage value of the sampling circuit output when the metal plate to be measured,/->The acquisition of the effective attenuation coefficient is a known technology, and the specific process is not repeated.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. An optimized correction method for X-ray thickness meter data is characterized by comprising the following steps:
acquiring a monitoring data time sequence of all monitoring data, wherein the monitoring data comprises a current value converted by X-ray intensity and a voltage value converted by environmental noise sound waves;
acquiring a modal component decomposition result corresponding to each voltage value sequence converted by the environmental noise sound wave by using an empirical mode decomposition algorithm; acquiring a first characteristic coefficient of measurement interference of each modal component according to the amplitude difference between corresponding spectrograms of different modal components in the decomposition result;
acquiring a measurement interference confidence coefficient according to the measurement interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the sound waves of the environmental noise;
acquiring the wavelet decomposition layer number according to the measurement interference confidence coefficient; obtaining a clean current signal based on the wavelet decomposition layer number by utilizing a wavelet denoising algorithm; and obtaining a correction result of the thickness gauge data according to the clean current signal.
2. The method for optimizing and correcting the data of the X-ray thickness gauge according to claim 1, wherein the method for obtaining the modal component decomposition result corresponding to each voltage value sequence converted by the sound wave of the environmental noise by using the empirical mode decomposition algorithm is as follows:
and taking the voltage value sequence converted by each environmental noise sound wave as the input of an empirical mode decomposition algorithm, and acquiring a preset number of mode components corresponding to the voltage value sequence by using the empirical mode decomposition algorithm.
3. The method for optimizing and correcting data of an X-ray thickness gauge according to claim 1, wherein the method for obtaining the first characteristic coefficient of measurement interference of each modal component according to the amplitude difference between corresponding spectrograms of different modal components in the decomposition result is as follows:
acquiring a measured interference coefficient and a measured interference difference coefficient of each modal component according to a spectrogram of each modal component in a modal component decomposition result corresponding to each voltage value sequence converted by the sound waves of the environmental noise;
taking the difference value of the measured interference coefficient between each modal component and any one of the rest modal components as a first difference value; taking the difference value between the measured interference difference coefficient between each modal component and any one of the rest modal components as a second difference value; the sum of the products of the first difference and the second difference over all the remaining one modal component is taken as the measured interference first characteristic coefficient for each modal component.
4. The method for optimizing and correcting the data of the X-ray thickness gauge according to claim 3, wherein the method for obtaining the measured interference coefficient and the measured interference difference coefficient of each modal component according to the spectrogram of each modal component in the modal component decomposition result corresponding to the voltage value sequence converted by each environmental noise acoustic wave is as follows:
carrying out Fourier transform on each modal component to obtain a spectrogram of each modal component, and taking an amplitude corresponding to a frequency minimum value in the spectrogram of each modal component as a measurement interference coefficient of each modal component;
and taking the difference value between the maximum amplitude value and the minimum amplitude value in the spectrogram of each modal component as a measured interference difference coefficient of each modal component.
5. The method for optimizing and correcting the data of the X-ray thickness gauge according to claim 1, wherein the method for obtaining the measurement interference confidence coefficient according to the measurement interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the sound wave of the environmental noise is as follows:
acquiring a first characteristic difference sequence of each voltage value sequence converted by the environmental noise sound waves according to the measured interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the environmental noise sound waves;
acquiring interference complexity between two environmental noise sound waves according to a first characteristic difference sequence of a voltage value sequence converted by the two environmental noise sound waves;
taking the average value of interference complexity among all the environmental noise sound waves as a measurement interference confidence coefficient.
6. The method for optimizing and correcting data of an X-ray thickness gauge according to claim 5, wherein the method for obtaining the first characteristic difference sequence of each voltage value sequence converted by the environmental noise sound wave according to the measurement interference first characteristic coefficient of each modal component corresponding to each voltage value sequence converted by the environmental noise sound wave comprises the following steps:
the measurement interference first characteristic difference coefficient of each modal component of each voltage value sequence converted by the environmental noise sound wave is used as the first characteristic difference sequence of the voltage value sequence converted by the environmental noise sound wave according to the sequence formed by the small-to-large sequence.
7. The method for optimizing and correcting data of an X-ray thickness gauge according to claim 5, wherein the method for obtaining the interference complexity between two environmental noise sound waves according to the first characteristic difference sequence of the voltage value sequences converted by the two environmental noise sound waves is as follows:
taking the measurement distance between the first characteristic difference sequences of the two voltage value sequences converted by the sound waves of the environmental noise as a first interference difference value;
taking the difference value between the average values of the elements in the first characteristic difference sequence of the two voltage value sequences converted by the sound waves of the environmental noise as a second interference difference value;
the interference complexity between two environmental noise sound waves consists of a first interference difference value and a second interference difference value, wherein the interference complexity is in direct proportion to the first interference difference value and the second interference difference value.
8. The method for optimizing and correcting the data of the X-ray thickness gauge according to claim 1, wherein the method for obtaining the wavelet decomposition layer number according to the measurement interference confidence coefficient is as follows:
taking the product of the measured interference confidence coefficient and the preset parameter as the input of a rounding function, and taking the output of the rounding function as the number of layers of wavelet decomposition.
9. The method for optimizing and correcting the data of the X-ray thickness gauge according to claim 1, wherein the method for obtaining the clean current signal based on the wavelet decomposition layer number by utilizing the wavelet denoising algorithm is as follows:
and taking the current signal acquired in the receiver of the thickness gauge as the input of a wavelet denoising algorithm, and obtaining a clean current signal based on the number of layers of the obtained wavelet decomposition by using the wavelet denoising algorithm.
10. The method for optimizing and correcting the data of the X-ray thickness gauge according to claim 1, wherein the method for obtaining the correction result of the data of the thickness gauge according to the clean current signal is as follows:
and processing the clean current signal by a signal conversion unit and a computer in the X-ray thickness meter to obtain a measurement result of the metal plate to be measured as a correction result of the thickness meter data.
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